Area separating apparatus, image processing apparatus employing the same, and area separating method

ABSTRACT

An area separating apparatus for judging whether or not each object pixel belongs to a photograph image area in an image. The apparatus comprises: an average value calculating circuit for calculating an average value of image data of pixels in an image block containing the object pixel; a photograph image area judgment threshold generating circuit for generating a photograph image area judgment threshold in accordance with the average value; a density difference summing circuit for determining differences in image data between respective adjacent pairs of pixels in the image block and calculating a sum of the image data differences for all the pixels in the image block; and a judgment circuit which judges that the object pixel belongs to the photograph image area if the sum of the image data differences is smaller than the photograph image area judgment threshold, and judges that the object pixel does not belong to the photograph image area if the sum of the image data differences is not smaller than the photograph image area judgment threshold.

BACKGROUND OF THE INVENTION

[0001] 1. Field of the Invention

[0002] The present invention relates to an area separating apparatus andan area separating method for judging whether or not each pixel belongsto a photograph image area or whether or not each pixel belongs to athin line image area for use in an image processing apparatus forperforming a so-called pseudo-halftoning process on image data. Theinvention further relates to an image processing apparatus employingsuch an area separating apparatus and method.

[0003] 2. Description of Related Art

[0004] In image forming apparatuses such as digital copying machines,printers and facsimile machines, a so-called pseudo-halftoning processis performed when multi-level image data indicative of density gradationlevels is converted into two-level image data. Particularly, multi-levelimage data representing a photograph image includes a lot of halftoneimage data, so that the pseudo-halftoning process is indispensable. Oneexample of the pseudo-halftoning process is an error diffusion process.

[0005] In the error diffusion process, an error generated whenmulti-level image data of an object pixel is converted into two-levelimage data with the use of a predetermined threshold is diffused toperipheral pixels yet to be subjected to the two-level quantizationaround the object pixel for modifying multi-level image data of theperipheral pixels, and this error diffusing operation is repeatedlyperformed. Thus, the density of dots to be outputted from an imageforming section is properly controlled, whereby an image represented ona pseudo-halftone basis is outputted. Image forming sections are mostlyadapted to form an image on a recording sheet through anelectrophotographic process.

[0006] In an ordinary error diffusion process, dot distribution is atrandom, resulting in generation of a lot of isolated dots. In the imageformation through the electrophotographic process, however, it isimpossible to accurately control the size of each of the isolated dots,because dots in an image do not always have a stable size. Where theordinary error diffusion process is applied to the image formationthrough the electrophotographic process, gradation representation cannotsatisfactorily be stabilized. Therefore, the ordinary error diffusionprocess is not always suitable for reproduction of a photograph image.

[0007] Another example of the halftoning process is an organizeddithering process. The organized dithering process includes a dotdistribution method (frequency modulation method) in which dots havingthe same size are distributed at various densities in accordance withgradation levels, and a dot concentration method (amplitude modulationmethod) in which dots having different diameters according to gradationlevels are arranged with the centers thereof being equidistantly spacedfrom one another. Of these methods, the dot concentration method is moresuitable for halftone representation through the electrophotographicprocess in consideration of the stabilization of the gradationrepresentation.

SUMMARY OF THE INVENTION

[0008] In Japanese Patent Application No. 11-352825 (1999) previouslyfiled, the inventors of the present invention have proposed an improvederror diffusion process in which a threshold to be employed for atwo-level quantization process is periodically two-dimensionally variedfor enhancement of the dot concentration degree. In the improved errordiffusion process, dots are liable to be periodically concentrated, sothat a so-called dotting process can be performed. Although theorganized dithering process poses a problem associated with theresolution of character images and diagrammatic images, the improvederror diffusion process can ensure satisfactory resolution of thecharacter images and the diagrammatic images.

[0009] By employing the improved error diffusion process for thepseudo-halftoning process, the image processing can advantageously besimplified without the need for performing different processingoperations depending on the type of an image area to which a pixelbelongs to.

[0010] The periodic variation of the two-level quantization threshold ismainly intended for improvement of gradation representation ofphotograph images, and the dot concentration resulting from the periodicvariation does not always produce an advantageous effect on a characterimage area and a halftone dot image area. For example, a so-called moirépattern is generated in a halftone dot image area with a lower linefrequency (e.g., a halftone dot image area with a line frequency of nothigher than 150 lines per inch (lpi)) due to interference by theperiodic variation of the two-level quantization threshold.

[0011] For further improvement of image quality, it is preferred toaccurately separate a photograph image area from the other image areas(i.e., a character image area, a diagrammatic image area and alower-line-frequency halftone dot image area) and perform optimizedhalftoning operations on the respective image areas.

[0012] It is herein defined that the photograph image area includes notonly an original photograph image area but also a halftone dot imagearea with a higher line frequency. The higher-line-frequency halftonedot image area has a line frequency such that dots in the halftone dotimage area cannot be visually identified from a distance of about 25centimeters, typically 175 lpi or higher. Halftone dot images with linefrequencies of 175 lpi to 200 lpi are typically employed for printing ofart books.

[0013] It is an object of the present invention to provide an areaseparating apparatus and an area separating method which ensure accuratediscrimination of a pixel belonging to a photograph image area.

[0014] It is another object of the present invention to provide an imageprocessing apparatus which is capable of performing optimized halftoningoperations for respective image areas by accurately discriminating apixel belonging to a photograph image area from pixels belonging toimage areas other than the photograph image area.

[0015] The area separating apparatus according to the present inventionis adapted to judge whether or not each object pixel belongs to aphotograph image area in an image on the basis of image data indicativeof density gradation levels of pixels constituting the image, andcomprises: an average value calculating circuit (S1) for calculating anaverage value of image data of pixels in a first image block of apredetermined size containing the object pixel; a photograph image areajudgment threshold generating circuit (40) for generating a photographimage area judgment threshold in accordance with the average valuecalculated by the average value calculating circuit; a densitydifference summing circuit (S2) for determining differences in imagedata between respective adjacent pairs of pixels in the image block andcalculating a sum of the image data differences for all the pixels inthe image block; and a first judgment circuit (S4) for judging that theobject pixel belongs to the photograph image area if the sum of theimage data differences calculated by the density difference summingcircuit is smaller than the photograph image area judgment thresholdgenerated by the photograph image area judgment threshold generatingcircuit, and judging that the object pixel does not belong to thephotograph image area if the sum of the image data differences is notsmaller than the photograph image area judgment threshold. Parenthesizedalphanumeric characters denote components corresponding to thosedescribed later in the embodiment of the invention, but do not intend tolimit the invention to the embodiment. This definition is effectual inthis section.

[0016] With this arrangement, whether or not the object pixel belongs tothe photograph image area is judged on the basis of the average value ofthe image data of the pixels in the first image block of thepredetermined size containing the object pixel and the sum of the imagedata differences between the respective adjacent pairs of pixels in theimage block. More specifically, if the sum of the image data differencesis not smaller than the photograph image area judgment thresholddetermined in accordance with the average value of the image data, it isjudged that the sum of the image data differences is relatively greatwith respect to an image density in the image block and, hence, theobject pixel does not belong to the photograph image area. On thecontrary, if the sum of the image data differences is smaller than thephotograph image area judgment threshold, it is judged that a densityvariation in the first image block is relatively small and, hence, theobject pixel belongs to the photograph image area. Thus, whether or noteach of the pixels belongs to the photograph image area can accuratelybe judged.

[0017] The size of the first image block is preferably such as toaccommodate at least one halftone dot in a halftone dot image with aminimum line frequency desired to be discriminated from the photographimage area. Further, the size of the first image block is preferablydetermined so that distributions of plots indicative of a relationshipbetween the average value of the image data and the sum of the imagedata differences for the photograph image area and for the other imageareas appear in separate regions in a distribution graph.

[0018] In accordance with a first embodiment of the present invention,the apparatus further comprises: a first direction density differencesumming circuit (S3) for determining differences in image data betweenrespective adjacent pairs of pixels aligning in a first direction in asecond image block of a predetermined size containing the object pixeland summing the image data differences for all the pixels in the secondimage block for determination of a first direction density differencesum (H_SUM); a second direction density difference summing circuit (S3)for determining differences in image data between respective adjacentpairs of pixels aligning in a second direction different from the firstdirection in the second image block and summing the image datadifferences for all the pixels in the second image block fordetermination of a second direction density difference sum (V_SUM); anda second judgment circuit (S5, S6) for judging whether or not the objectpixel belongs to a thin line image area on the basis of a magnituderelationship between the first direction density difference sum and thesecond direction density difference sum respectively calculated by thefirst direction density difference summing circuit and the seconddirection density difference summing circuit.

[0019] With this arrangement, the image data differences between therespective adjacent pairs of pixels aligning in the first direction(e.g., a main scanning direction at image reading) in the second imageblock of the predetermined size containing the object pixel aredetermined. Then, the image data differences are summed fordetermination of the first direction density difference sum.

[0020] On the other hand, the image data differences between therespective adjacent pairs of pixels aligning in the second direction(e.g., a sub-scanning direction at the image reading) in the secondimage block are determined. Then, the image data differences for all thepixels in the second image block are summed for determination of thesecond direction density difference sum. Then, whether or not the objectpixel is a constituent pixel of a thin line image area, i.e., whether ornot the object pixel belongs to the thin line image area, is judged onthe basis of the magnitude relationship between the first and seconddirection density difference sums.

[0021] More specifically, the second judgment circuit compares the firstdirection density difference sum calculated by the first directiondensity difference summing circuit and the second direction densitydifference sum calculated by the second direction density differencesumming circuit with a pair of first direction judgment thresholds HL,HH (HL<HH) and a pair of second direction judgment thresholds VL, VH(VL<VH), respectively, and judges that the object pixel belongs to thethin line image area if a condition that the first direction densitydifference sum is not smaller than the first direction judgmentthreshold HH and the second direction density difference sum is notgreater than the second direction judgment threshold VL is satisfied(YES in S5), or if a condition that the first direction densitydifference sum is not greater than the first direction judgmentthreshold HL and the second direction density difference sum is notsmaller than the second direction judgment threshold VH is satisfied(YES in S6). If neither of the conditions is satisfied, the secondjudgment circuit judges that the object pixel does not belong to thethin line image area.

[0022] That is, if the first direction density difference sum isrelatively great and the second direction density difference sum isrelatively small, there is a high possibility that the object pixelbelongs to a thin line image area in which many thin lines eachextending in the second direction are present. On the other hand, if thefirst direction density difference sum is relatively small and thesecond direction density difference sum is relatively great, there is ahigh possibility that the object pixel belongs to a thin line image areain which many thin lines each extending in the first direction arepresent. Thus, the judgment can properly be made in the case where theobject pixel belongs to the thin line image area, i.e., the object pixeldoes not belong to the photograph image area.

[0023] The size of the second image block is preferably determined sothat distributions of plots indicative of a relationship between thefirst direction density difference sum and the second direction densitydifference sum for the photograph image area and for the thin line imagearea appear in separate regions in a distribution graph.

[0024] The first direction and the second direction are preferablyorthogonal to each other. The first direction may be the main scanningdirection at the image reading. In this case, the second direction ispreferably the sub-scanning direction at the image reading.Alternatively, the first direction may be oriented obliquely (forexample, at 45 degrees) with respect to the main scanning direction atthe image reading. In this case, the second direction is orthogonal tothe first direction (for example, oriented obliquely at 135 degrees withrespect to the main scanning direction).

[0025] The apparatus preferably further comprises an integrator circuit(39) for performing an integration process on image data of the objectpixel with the use of the image data of the object pixel and image dataof peripheral pixels around the object pixel, and a judgment ispreferably made on the basis of the image data pre-processed by theintegrator circuit to determine which of the image areas the objectpixel belongs to.

[0026] With this arrangement, the pre-processing operation (smoothingprocess) is performed by the integrator circuit, whereby a halftone dotimage with a higher line frequency can assuredly be judged to belong tothe photograph image area.

[0027] Where the image data is subjected to a halftoning process (37),the halftoning process may be a dotting process (e.g., the organizeddithering process of dot concentration type or the improved errordiffusion process) which is performed on the basis of a predeterminedline frequency on pixels judged to belong to the photograph image area.In this case, the area separating apparatus preferably further comprisesa pre-judgment circuit (39) for defining a boundary line frequencybetween the predetermined line frequency and the predetermined linefrequency plus 50 lpi, and excluding pixels constituting a halftone dotimage with a line frequency lower than the boundary line frequency fromthe pixels judged to belong to the photograph image area.

[0028] With this arrangement, the boundary line frequency is definedbetween the line frequency employed for the dotting process in thehalftoning process and this line frequency plus 50 lpi, and the pixelsin the halftone dot image with the line frequency lower than theboundary line frequency are excluded from the pixels judged to belong tothe photograph image area. Thus, a moiré pattern can be prevented whichmay otherwise be generated by the dotting process to be performed on aphotograph image.

[0029] The pre-judgment circuit may be adapted to perform the aforesaidoperation on the image data to be subjected to the halftoning process.

[0030] The pre-judgment circuit may include an integration filter (39)for performing a smoothing process on the image data so as to causehalftone dots constituting a halftone dot image with a line frequencynot lower than the boundary line frequency to contact one another.

[0031] With this arrangement, the halftone dot image with the linefrequency not lower than the boundary line frequency defined between theline frequency employed for the dotting process in the halftoningprocess and this line frequency plus 50 lpi can be subjected to theintegration process so that the halftone dots in this halftone dot imageare linked to one other. On the other hand, halftone dots in a halftonedot image with a line frequency lower than the boundary line frequencycan be prevented from being linked to one another. The simplepre-processing operation with the use of the integration filter makes itpossible to assuredly judge that the higher-line-frequency halftone dotimage belongs to the photograph image area, and to judge that thehalftone dot image with a line frequency liable to cause a morié patterndoes not belong to the photograph image area.

[0032] The image processing apparatus according to the present inventioncomprises: an area separating apparatus having the aforesaid features;and a halftoning circuit (37) for performing a dot concentrationhalftoning process (e.g., the organized dithering process of dotconcentration type or the improved dotting process) on pixels judged tobelong to the photograph image area by the area separating apparatus andperforming a dot distribution half toning process (e.g., the ordinaryerror diffusion process) on pixels judged not to belong to thephotograph image area by the area separating apparatus.

[0033] With this arrangement, the pixels judged to belong to thephotograph image area are subjected to the dot concentration halftoningprocess, whereby a photograph image can be reproduced with excellentgradation representation. On the other hand, the pixels judged not tobelong to the photograph image area are subjected the dot distributionhalftoning process, whereby a character image, a diagrammatic image anda lower-line-frequency halftone dot image can be reproduced with anexcellent resolution.

[0034] The foregoing and other objects, features and effects of thepresent invention will become more apparent from the followingdescription of the preferred embodiment with reference to the attacheddrawings.

BRIEF DESCRIPTION OF THE DRAWINGS

[0035]FIG. 1 is a block diagram illustrating the electrical constructionof a digital copying machine which is one example of an image formingapparatus employing an image processing apparatus according to oneembodiment of the present invention;

[0036]FIG. 2 is a block diagram for explaining the functionalconfiguration of an image processing section;

[0037]FIG. 3 is a flow chart for explaining a process to be performed byan area separating section;

[0038]FIG. 4 is a diagram illustrating a first image block (13×7 pixelmatrix) to be employed for extraction of pixels in a photograph imagearea;

[0039]FIG. 5 is a diagram illustrating a second image block (5×5 pixelmatrix) to be employed for extraction of pixels in a thin line imagearea;

[0040]FIG. 6 is a graph for explaining how to determine a thresholdTH(AV) to be employed for discrimination of a photograph image area withrespect to an average value AV of image data of pixels within the firstimage block;

[0041]FIG. 7 is a diagram illustrating distributions of plots indicativeof a relationship between a main scanning direction density differencesum H_SUM and a sub-scanning direction density difference sum V_SUM forthe second image block;

[0042] FIGS. 8(a) and 8(b) are diagrams for explaining the constructionof a pre-separation filtering section;

[0043]FIG. 9 is a diagram for explaining a process to be performed bythe pre-separation filtering section;

[0044]FIG. 10 is a diagram for explaining the size of a matrix of thefirst image block;

[0045]FIG. 11 is a block diagram for explaining the functionalconfiguration of a halftoning section;

[0046] FIGS. 12(a) and 12(b) are diagrams for explaining accumulationand distribution of quantization errors;

[0047]FIG. 13 is a block diagram for explaining the functionalconfiguration of a parameter generating section;

[0048]FIG. 14(a) is a diagram illustrating a variable threshold matrixstored in a variable threshold matrix memory, and FIG. 14(b) is adiagram illustrating addresses of the variable threshold matrix memorycorresponding to respective matrix positions in the variable thresholdmatrix;

[0049]FIG. 15 is a diagram illustrating exemplary settings for variablethreshold tables T1, T2 and T3;

[0050]FIG. 16 is a diagram illustrating periodic variation ofquantization thresholds and corresponding periodic variation of errorcalculation reference values; and

[0051]FIG. 17 is a diagram for explaining an effect of a higher-levelquantization process to be performed for a specific matrix element valuein the variable threshold matrix.

DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0052]FIG. 1 is a block diagram illustrating the electrical constructionof a digital copying machine which is one example of an image formingapparatus employing an image processing apparatus according to oneembodiment of the present invention. The digital copying machine has areading section 1 including a photoelectric converter (e.g., a linesensor such as a CCD) for reading an optical image of a documentoriginal and converting the optical image into electric signals.

[0053] The electric signals outputted from the reading section 1 areinputted to an analog circuit 2 having an auto gain control (AGC)circuit 21 and an analog/digital (A/D) converter 22. The AGC circuit 21functions to amplify the minute analog electric signals from the readingsection 1 to a level within an A/D conversion range (reference voltage)of the A/D converter 22. The A/D converter 22 quantizes the electricsignals amplified by the AGC circuit 21 for generation of digital imagesignals. For example, a signal of a minute amplitude (1 volt) outputtedfrom the reading section 1 is amplified to an electric signal of a5-volt amplitude by the AGC circuit 21, and quantized on a 8-bit basisinto 0 (00h) to 255 (FFh)) by the A/D converter 22. Thus, digital imagedata is generated which has a density gradation level represented on a256-level basis.

[0054] The image data is subjected to various image processingoperations by an image processing section 3, and then applied to anoutput section 4. The output section 4 includes, for example, a laserscanning unit. That is, the digital copying machine has an image formingsection for forming a copy image of the document original through anelectrophotographic process. The image forming section includes aphotoreceptor, the laser scanning unit for forming an electrostaticlatent image corresponding to the copy image of the document original onthe photoreceptor, a developer unit provided around the photoreceptor, atransfer unit, and a cleaning unit. The electrostatic latent imageformed on the photoreceptor by the laser scanning unit is developed intoa toner image by the developer unit. The toner image is transferred ontoa surface of a recording sheet such as a paper sheet or an OHP sheet(transparent sheet) in the transfer unit. The transferred toner image issubjected to a heat and press process thereby to be fixed on therecording sheet by a fixing unit.

[0055] The reading section 1 includes a light source for illuminatingthe document original, and an optical system for focusing lightreflected from the document original onto a detection surface of theline sensor. The reading section 1 is adapted to perform a main scanningoperation on the document original by electrical scanning of the linesensor and to perform a sub-scanning operation on the document originalby movement of the line sensor and the optical system with respect tothe document original. Of course, the sub-scanning operation on thedocument original may be achieved by moving the light source and theoptical system or by moving the document original with the light sourceand the optical system kept stationary.

[0056]FIG. 2 is a block diagram for explaining the functionalconfiguration of the image processing section 3. The image processingsection 3 includes a shading correction section 31, an input γcorrection section 32, a white/black reversing section 33, a zoomingsection 34, a filtering section 35, an output γ correction section 36,and a halftoning section 37, which successively perform predeterminedprocesses on the inputted image data.

[0057] The image processing section 3 further includes an areaseparating section 38 for judging whether or not a pixel for theinputted image data is a constituent pixel of a photograph image area,and a pre-separation filtering section 39 for pre-processing the imagedata to be supplied to the area separating section 38. The result of thejudgment made by the area separating section 38 is inputted to thefiltering section 35, the output γ correction section 36 and thehalftoning section 37. The filtering section 35, the output γ correctionsection 36 and the halftoning section 37 each perform the predeterminedprocess in different manners depending on whether or not the pixel forthe inputted image data belongs to the photograph image area.

[0058] Even when a blank image is read, analog signals outputted fromthe reading section 1 are not uniform with respect to the main scanningdirection. This is because the light source and the optical system eachhave different light distribution characteristics in a middle portionand end portions thereof with respect to the main scanning direction,and the line sensor has pixel-to-pixel sensitivity variations forreading. The shading correction section 31 makes a correction forpixel-to-pixel image data variations attributed to the characteristicsof the reading section 1.

[0059] The image data processed by the shading correction section 31 issubjected to an intensity-to-density converting process performed by theinput γ correction section 32. The input γ correction section 32 makes acorrection for the reading characteristics of the reading section 1 forgeneration of image data having a gradation characteristic proportionalto the density of the document original.

[0060] The white/black reversing section 33 reverses a white/black logicof the inputted image data. The reading section 1 outputs a lowervoltage for a high density portion (black area) of the documentoriginal. The higher the density of the document original, the lower theoutput voltage of the reading section 1. By reversing the logic of theimage data, the white/black reversing section 33 converts the image dataso that the value of the image data increases as the density of theimage increases.

[0061] The zooming section 34 carries out a zooming function through adigital process.

[0062] The filtering section 35 performs an edge emphasizing process ora smoothing process on the image data. In this embodiment, the filteringsection 35 receives an area separation signal inputted from the areaseparating section 38. Depending on the area separation signal, thefiltering section 35 performs the smoothing process on a pixel belongingto the photograph image area, and the edge emphasizing process on apixel belonging to any other image area. Thus, the photograph image areacan be reproduced with smooth gradation representation, while acharacter image area, a diagrammatic image area and a halftone dot imagearea with a lower line frequency can be reproduced with a properresolution.

[0063] The output γ correction section 36 processes the image data tomake a correction for the γ characteristic of an output engine in theoutput section 4. In the electrophotographic process, it is difficult toobtain an image density output linearly variable with respect to theinputted image data because of the charging properties of thephotoreceptor and toner. The correction for the γ characteristic of theoutput engine makes it possible to obtain an image density outputsubstantially linearly variable with respect to the inputted image data.

[0064] The halftoning section 37 converts (quantizes) the image datahaving a density represented on the basis of 256 gradation levels into adiscrete value on the basis of not smaller than 2 levels and smallerthan 256 levels for a so-called pseudo-halftoning process. In thisembodiment, the halftoning section 37 is adapted to perform a two-levelquantization process in principle and to perform a four-levelquantization process as required.

[0065] More specifically, the halftoning section 37 is adapted toselectively perform an ordinary error diffusion process by employingquantization thresholds each fixed at a predetermined value and animproved error diffusion process (a dotting process or a dotconcentration halftoning process) by employing quantization thresholdsperiodically two-dimensionally variable. In the improved error diffusionprocess, a two-level error diffusion process is basically performed, anda four-level quantization process (four-level error diffusion process)is performed on pixels adjacent to a dot concentrated area so that dotexpansion and contraction can be controlled at an increased number oflevels.

[0066] The selection of the ordinary error diffusion process and theimproved error diffusion process to be performed by the halftoningsection 37 is based on the area separation signal outputted from thearea separating section 38. That is, image data of a pixel belonging tothe photograph image area is subjected to the improved error diffusionprocess, while image data of a pixel belonging to any of the other imageareas is subjected to the ordinary error diffusion process.

[0067]FIG. 3 is a flow chart for explaining the process to be performedby the area separating section 38. Constituent pixels of a documentoriginal image read by the reading section 1 are sequentially extractedas an object pixel in a reading order by the area separating section 38,which in turn judges whether or not the object pixel belongs to thephotograph image area. For this purpose, an average value of image dataof pixels in a first image block of a predetermined size containing theobject pixel is first calculated (Step S1).

[0068] The first image block may be a 13×7 pixel matrix consisting ofpixels A1 to A13, B1 to B13, C1 to C13, D1 to D13, E1 to E13, F1 to F13and G1 to G13 retained in a proper buffer memory with the object pixelD7 located at the center thereof as shown in FIG. 4. In this case, theaverage value AV of the image data of the pixels in the first imageblock of the 13×7 pixel matrix is calculated from the followingexpression (1): $\begin{matrix}\begin{matrix}{{AV} = \quad \left( {{A1} + {A2} + {A3} + {A4} + {A5} + {A6} + {A7} + {A8} + {A9} +} \right.} \\{\quad {{A10} + {A11} + {A12} + {A13} + {B1} + {B2} + {B3} + {B4} +}} \\{\quad {{B5} + {B6} + {B7} + {B8} + {B9} + {B10} + {B11} + {B12} + {B13} +}} \\{\quad {{C1} + {C2} + {C3} + {C4} + {C5} + {C6} + {C7} + {C8} + {C9} +}} \\{\quad {{C10} + {C11} + {C12} + {C13} + {D1} + {D2} + {D3} + {D4} +}} \\{\quad {{D5} + {D6} + {D7} + {D8} + {D9} + {D10} + {D11} + {D12} + {D13} +}} \\{\quad {{E1} + {E2} + {E3} + {E4} + {E5} + {E6} + {E7} + {E8} + {E9} +}} \\{\quad {{E10} + {E11} + {E12} + {E13} + {F1} + {F2} + {F3} + {F4} +}} \\{\quad {{F5} + {F6} + {F7} + {F8} + {F9} + {F10} + {F11} + {F12} + {F13} +}} \\{\quad {{G1} + {G2} + {G3} + {G4} + {G5} + {G6} + {G7} + {G8} + {G9} +}} \\{\left. \quad {{G10} + {G11} + {G12} + {G13}} \right) \div \left( {13 \times 7} \right)}\end{matrix} & (1)\end{matrix}$

[0069] The area separating section 38 determines differences in imagedata between respective adjacent pairs of pixels in the first imageblock of the 13×7 pixel matrix, and calculates a sum of the image datadifferences for all the pixels in the matrix (Step S2).

[0070] More specifically, the area separating section 38 calculates asum TOTAL_DH of image data differences between pixels aligning in themain scanning direction of the reading section 1 from the followingexpression (2), and calculates a sum TOTAL_DV of image data differencesbetween pixels aligning in the sub-scanning direction of the readingsection 1 from the following expression (3). Then, these sums aretotaled for determination of the sum TOTAL_SUM of the image datadifferences in the 13×7 pixel matrix (see the following expression (4)).Of course, the sum TOTAL_SUM of the image data differences may directlybe determined without the determination of TOTAL_DH and TOTAL_DV.$\begin{matrix}\begin{matrix}{{TOTAL\_ DH} = \quad {{{{A1} - {A2}}} + {{{A2} - {A3}}} + {{{A3} - {A4}}} + {{{A4} - {A5}}} + {{{A5} -}}}} \\{{\quad {{A6}}} + {{{A6} - {A7}}} + {{{A7} - {A8}}} + {{{A8} - {A9}}} + {{{A9} - {A10}}} +} \\{\quad {{{{A10} - {A11}}} + {{{A11} - {A12}}} + {{{A12} - {A13}}} + {{{B1} - {B2}}} +}} \\{\quad {{{{B2} - {B3}}} + {{{B3} - {B4}}} + {{{B4} - {B5}}} + {{{B5} - {B6}}} + {{{B6} -}}}} \\{{\quad {{B7}}} + {{{B7} - {B8}}} + {{{B8} - {B9}}} + {{{B9} - {B10}}} + {{{B10} -}}} \\{{\quad {{B11}}} + {{{B11} - {B12}}} + {{{B12} - {B13}}} + {{{C1} - {C2}}} + {{{C2} -}}} \\{{\quad {{C3}}} + {{{C3} - {C4}}} + {{{C4} - {C5}}} + {{{C5} - {C6}}} + {{{C6} - {C7}}} +} \\{\quad {{{{C7} - {C8}}} + {{{C8} - {C9}}} + {{{C9} - {C10}}} + {{{C10} - {C11}}} +}} \\{\quad {{{{C11} - {C12}}} + {{{C12} - {C13}}} + {{{D1} - {D2}}} + {{{D2} - {D3}}} +}} \\{\quad {{{{D3} - {D4}}} + {{{D4} - {D5}}} + {{{D5} - {D6}}} + {{{D6} - {D7}}} +}} \\{\quad {{{{D7} - {D8}}} + {{{D8} - {D9}}} + {{{D9} - {D10}}} + {{{D10} - {D11}}} +}} \\{\quad {{{{D11} - {D12}}} + {{{D12} - {D13}}} + {{{E1} - {E2}}} + {{{E2} - {E3}}} +}} \\{\quad {{{{E3} - {E4}}} + {{{E4} - {E5}}} + {{{E5} - {E6}}} + {{{E6} - {E7}}} + {{{E7} -}}}} \\{{\quad {{E8}}} + {{{E8} - {E9}}} + {{{E9} - {E10}}} + {{{E10} - {E11}}} + {{{E11} -}}} \\{{\quad {{E12}}} + {{{E12} - {E13}}} + {{{F1} - {F2}}} + {{{F2} - {F3}}} + {{{F3} -}}} \\{{\quad {{F4}}} + {{{F4} - {F5}}} + {{{F5} - {F6}}} + {{{F6} - {F7}}} + {{{F7} - {F8}}} +} \\{\quad {{{{F8} - {F9}}} + {{{F9} - {F10}}} + {{{F10} - {F11}}} + {{{F11} - {F12}}} +}} \\{\quad {{{F12} - {F13}}}}\end{matrix} & (2) \\\begin{matrix}{{TOTAL\_ DV} = \quad {{{{A1} - {B1}}} + {{{B1} - {C1}}} + {{{C1} - {D1}}} + {{{D1} - {E1}}} + {{{E1} -}}}} \\{{\quad {{F1}}} + {{{F1} - {G1}}} + {{{A2} - {B2}}} + {{{B2} - {C2}}} + {{{C2} - {D2}}} +} \\{\quad {{{{D2} - {E2}}} + {{{E2} - {F2}}} + {{{F2} - {G2}}} + {{{A3} - {B3}}} + {{{B3} -}}}} \\{{\quad {{C3}}} + {{{C3} - {D3}}} + {{{D3} - {E3}}} + {{{E3} - {F3}}} + {{{F3} - {G3}}} +} \\{\quad {{{{A4} - {B4}}} + {{{B4} - {C4}}} + {{{C4} - {D4}}} + {{{D4} - {E4}}} + {{{E4} -}}}} \\{{\quad {{F4}}} + {{{F4} - {G4}}} + {{{A5} - {B5}}} + {{{B5} - {C5}}} + {{{C5} - {D5}}} +} \\{\quad {{{{D5} - {E5}}} + {{{E5} - {F5}}} + {{{F5} - {G5}}} + {{{A6} - {B6}}} + {{{B6} -}}}} \\{{\quad {{C6}}} + {{{C6} - {D6}}} + {{{D6} - {E6}}} + {{{E6} - {F6}}} + {{{F6} - {G6}}} +} \\{\quad {{{{A7} - {B7}}} + {{{B7} - {C7}}} + {{{C7} - {D7}}} + {{{D7} - {E7}}} + {{{E7} -}}}} \\{{\quad {{F7}}} + {{{F7} - {G7}}} + {{{A8} - {B8}}} + {{{B8} - {C8}}} + {{{C8} - {D8}}} +} \\{\quad {{{{D8} + {E8}}} + {{{E8} - {F8}}} + {{{F8} - {G8}}} + {{{A9} - {B9}}} + {{{B9} -}}}} \\{{\quad {{C9}}} + {{{C9} - {D9}}} + {{{D9} - {E9}}} + {{{E9} - {F9}}} + {{{F9} - {G9}}} +} \\{\quad {{{{A10} - {B10}}} + {{{B10} - {C10}}} + {{{C10} - {D10}}} + {{{D10} -}}}} \\{{\quad {{E10}}} + {{{E10} - {F10}}} + {{{F10} - {G10}}} + {{{A11} - {B11}}} +} \\{\quad {{{{B11} - {C11}}} + {{{C11} - {D11}}} + {{{D11} - {E11}}} + {{{E11} -}}}} \\{{\quad {{F11}}} + {{{F11} - {G11}}} + {{{A12} - {B12}}} + {{{B12} - {C12}}} +} \\{\quad {{{{C12} - {D12}}} + {{{D12} - {E12}}} + {{{E12} - {F12}}} + {{{F12} -}}}} \\{{\quad {{G12}}} + {{{A13} - {B13}}} + {{{B13} - {C13}}} + {{{C13} - {D13}}} +} \\{\quad {{{{D13} - {E13}}} + {{{E13} - {F13}}} + {{{F13} - {G13}}}}}\end{matrix} & (3) \\{{TOTAL\_ SUM} = {{TOTAL\_ DH} + {TOTAL\_ DV}}} & (4)\end{matrix}$

[0071] The area separating section 38 further judges whether or not theobject pixel belongs to the thin line image area (a horizontal thin lineimage area or a vertical thin line image area) to discriminate thehorizontal thin line image area and the vertical thin line image areafrom the photograph image area. The horizontal thin line image areaherein means an area in which horizontal lines extending parallel toeach other in the main scanning direction of the reading section 1 areformed at a high density. The vertical thin line image area herein meansan area in which vertical lines extending parallel to each other in thesub-scanning direction of the reading section 1 are formed at a highdensity.

[0072] For the judgment, the area separating section 38 determinesdifferences in image data between respective adjacent pairs of pixelsaligning in a first direction (e.g., main scanning direction) in asecond image block of a predetermined size containing the object pixel,and sums up the image data differences for all the pixels in the secondimage block for determination of a first direction density differencesum. Further, the area separating section 38 determines differences inimage data between respective adjacent pairs of pixels aligning in asecond direction (e.g., sub-scanning direction) orthogonal to the firstdirection in the second image block, and sums up the image datadifferences for all the pixels in the second image block fordetermination of a second direction density difference sum.

[0073] More specifically, the second image block is a 5 (pixels)×5(lines) matrix consisting of pixels B5 to B9, C5 to C9, D5 to D9, E5 toE9 and F5 to F9 retained in a proper buffer memory with the object pixelD7 located at the center thereof as shown in FIG. 5. A main scanningdirection density difference sum H_SUM and a sub-scanning directiondensity difference sum V_SUM are calculated as the first directiondensity difference sum and as the second direction density differencesum from the following expressions (5) and (6), respectively (Step S3 inFIG. 3). $\begin{matrix}\begin{matrix}{{H\_ SUM} = \quad {{{{B5} - {B6}}} + {{{B6} - {B7}}} + {{{B7} - {B8}}} + {{{B8} - {B9}}} +}} \\{\quad {{{{C5} - {C6}}} + {{{C6} - {C7}}} + {{{C7} - {C8}}} + {{{C8} - {C9}}} +}} \\{\quad {{{{D5} - {D6}}} + {{{D6} - {D7}}} + {{{D7} - {D8}}} + {{{D8} - {D9}}} +}} \\{\quad {{{{E5} - {E6}}} + {{{E6} - {E7}}} + {{{E7} - {E8}}} + {{{E8} - {E9}}} +}} \\{\quad {{{{F5} - {F6}}} + {{{F6} - {F7}}} + {{{F7} - {F8}}} + {{{F8} - {F9}}}}}\end{matrix} & (5) \\\begin{matrix}{{V\_ SUM} = \quad {{{{B5} - {C5}}} + {{{C5} - {D5}}} + {{{D5} - {E5}}} + {{{E5} - {F5}}} +}} \\{\quad {{{{B6} - {C6}}} + {{{C6} - {D6}}} + {{{D6} - {E6}}} + {{{E6} - {F6}}} +}} \\{\quad {{{{B7} - {C7}}} + {{{C7} - {D7}}} + {{{D7} - {E7}}} + {{{E7} - {F7}}} +}} \\{\quad {{{{B8} - {C8}}} + {{{C8} - {D8}}} + {{{D8} - {E8}}} + {{{E8} - {F8}}} +}} \\{\quad {{{{B9} - {C9}}} + {{{C9} - {D9}}} + {{{D9} - {E9}}} + {{{E9} - {F9}}}}}\end{matrix} & (6)\end{matrix}$

[0074] Subsequently, the area separating section 38 reads out a judgmentthreshold TH(AV) (photograph image area judgment threshold) defined as afunction of the average value AV determined in Step S1 with reference toa judgment threshold table 40 (see FIG. 2). The sum TOTAL_SUM of theimage data differences in the 13×7 pixel matrix is compared with thejudgment threshold TH(AV) thus read out (Step S4). If the sum TOTAL_SUMof the image data differences is not smaller than the judgment thresholdTH(AV) (NO in Step S4), it is judged that the object pixel is aconstituent pixel of an image belonging to any of the image areas otherthan the photograph image area (Step S7). Therefore, the area separatingsection 38 outputs an area separation signal (e.g., a 1-bit signalhaving a value of 0) indicative of this judgment.

[0075] On the other hand, if the sum TOTAL_SUM of the image datadifferences is smaller than the judgment threshold TH(AV) (YES in StepS4), it is temporarily judged that the object pixel D7 belongs to thephotograph image area. The validity of the judgment is judged again inSteps S5 and S6 which will be described later.

[0076]FIG. 6 is a graph for explaining how to determine the thresholdTH(AV) for the average value AV. FIG. 6 illustrates a relationshipbetween the average value AV and the sum TOTAL_SUM of the image datadifferences. An exemplary setting of the threshold TH(AV) for theaverage value AV is represented by a solid line. Plots indicative of arelationship between the average value AV and the sum TOTAL_SUM of theimage data differences for the photograph image area are denoted by asymbol “◯”, while plots indicative of a relationship between the averagevalue AV and the sum TOTAL_SUM of the image data differences for theimage areas other than the photograph image area (the character imagearea, the diagrammatic image area and the lower-line-frequency halftonedot image area) are denoted by a symbol “x”

[0077] As can be understood from FIG. 6, the threshold TH(AV) is setbetween a distribution region of the plots ◯ and a distribution regionof the plots x. Therefor, the object pixel is judged to belong to thephotograph image area if the sum TOTAL_SUM of the image data differencesis smaller than the threshold TH(AV). On the other hand, the objectpixel is judged to belong to any of the image areas other than thephotograph image area if the sum TOTAL_SUM of the image data differencesis not smaller than the threshold TH(AV) determined on the basis of theaverage value AV.

[0078] Referring again to FIG. 3, the area separating section 38determines a magnitude relationship between the main scanning directiondensity difference sum H_SUM and the sub-scanning direction densitydifference sum V_SUM each determined for the 5×5 pixel matrix of thesecond image block through the processes in Steps S5 and S6, and judgeswhether or not the object pixel D7 belongs to the thin line image areaon the basis of the result of the determination of the magnituderelationship. If the object pixel is judged to belong to the thin lineimage area, the area separating section 38 judges that the object pixelD7 does not belong to the photograph image area, and generates an areaseparation signal “0” indicative of this judgment.

[0079] More specifically, two thresholds HL and HH (HH>HL) are definedfor the main scanning direction density difference sum H_SUM and,similarly, two thresholds VL and VH (VH>VL) are defined for thesub-scanning direction density difference sum V_SUM as shown in FIG. 7.For example, the thresholds HL, HH; VL, VH are defined as follows:

HL=50 HH=150

VL=50 VH=100

[0080] In a plane with the sub-scanning direction density difference sumV_SUM and the main scanning direction density difference sum H_SUM beingplotted as abscissa and ordinate, respectively, as shown in FIG. 7,pixels constituting a horizontal thin line image area in which thinlines each extending horizontally (in the main scanning direction) arepresent at a high density are mostly plotted in a region HF where thesub-scanning direction density difference sum V_SUM is relatively greatand the main-scanning direction density difference sum H_SUM isrelatively small. Pixels belonging to a vertical thin line image area inwhich thin lines each extending vertically (in the sub-scanningdirection) are present at a high density are mostly plotted in a regionVF where the sub-scanning direction density difference sum V_SUM isrelatively small and the main-scanning direction density difference sumH_SUM is relatively great. Pixels in an original photograph image and ahalftone dot image to be regarded as belonging to the photograph imagearea are plotted in a central region PS of the V_SUM-H_SUM plane.

[0081] In this embodiment, if a condition that the main scanningdirection density difference sum H_SUM for the object pixel is notsmaller than the threshold HH and the sub-scanning direction densitydifference sum V_SUM is not greater than VL is satisfied (YES in Step S5in FIG. 3), the area separating section 38 judges that the object pixelbelongs to the thin line image area (in this case, the vertical thinline image area). That is, the area separating section 38 judges thatthe object pixel does not belong to the photograph image area, andgenerates an area separation signal “0” indicative of this judgment(Step S7).

[0082] If a condition that the main scanning direction densitydifference sum H_SUM for the object pixel is not greater than thethreshold HL and the sub-scanning direction density difference sum V_SUMis not smaller than VH is satisfied (YES in Step S6), the areaseparating section 38 judges that the object pixel belongs to the thinline image area (in this case, the horizontal thin line image area).That is, the area separating section 38 judges that the object pixeldoes not belong to the photograph image area, and generates an areaseparation signal “0” indicative of this judgment (Step S7).

[0083] If the judgments in Steps S5 and S6 are both negative (i.e., inthe case where the main scanning direction density difference sum H_SUMis not smaller than the threshold HH but the sub-scanning directiondensity difference sum V_SUM is greater than the threshold VL, in thecase where the main scanning direction density difference sum H_SUM isnot greater than the threshold HL but the sub-scanning direction densitydifference sum V_SUM is smaller than the threshold VH, or in the casewhere the main scanning direction density difference sum H_SUM is in therange between HL and HH), it is judged that the object pixel D7 does notbelong to the thin line image area. That is, the judgment is made againto determine that the object pixel D7 belongs to the photograph imagearea (Step S8). In this case, the area separating section 38 generates,for example, a 1-bit area separation signal having a value (“1” in thisembodiment) indicative of the attribution to the photograph image area.

[0084] Thus, the judgment based on the sum of the density differencesbetween the pixels in the 13×7 pixel matrix (YES in Step S4) isre-confirmed.

[0085] FIGS. 8(a) and 8(b) are diagrams for explaining the process to beperformed by the pre-separation filtering section 39. The pre-separationfiltering section 39 basically serves as integrator means for performingan integration filtering process. As shown in FIG. 8(a), image data ofan object pixel c3 is smoothed with the use of image data of 13 pixelsa3, b2 to b4, c1 to c5, d2 to d4 and e3 within a rhombus matrix (asquare matrix oriented obliquely at 45 degrees with respect to the mainscanning direction) with the object pixel c3 located at the center ofthe matrix.

[0086] Factors s1 to s6 by which the image data of the respective pixelswithin the matrix shown in FIG. 8(a) are to be multiplied are defined,for example, so as to be generally symmetric with respect to the objectpixel c3 in the main scanning direction and the sub-scanning directionas shown in FIG. 8(b). The factors s1 to s6 may be set at the same valueas shown below or at different values. For example, the values of thefactors s1 to s6 may differently be weighted depending on the distancefrom the object pixel.

s1=s2=s3=s4=s5=s6=1

[0087] Where the factors s1 to s6 are set at a value as defined by theabove expression, the image data of the object pixel c3 is convertedinto a value F (c3) defined by the following expression (7):

F(c3)={s1c3+s2(c2+c4)+s3(c1+c5)+s4(b3+d3)+s5(b2+b4+d2+d4)+s6(a3+e3)}÷13  (7)

[0088] In this embodiment, halftone dots are formed, for example, at ascreen angle of 45 degrees with a line frequency of 141 lpi in theimproved error diffusion process to be performed on the pixels belongingto the photograph image area by the halftoning section 37. On the otherhand, the reading section 1 has a reading resolution of 600 dpi (dotsper inch). Therefore, adjacent 141-lpi halftone dots are present atpositions corresponding to pixels p1, p2, as shown in FIG. 9, which areapart from each other by 3 pixels in the main scanning direction and inthe sub-scanning direction along a line extending obliquely at 45degrees with respect to these directions.

[0089] In general, dots are more stably formed, as the line frequency ofa halftone dot image to be subjected to the dotting process is closer tothe line frequency to be employed for the dotting process. In the imageoutputting apparatus, the line frequency to be employed for the dottingprocess is generally set at the greatest possible line frequency whichensures the image reproducibility of the apparatus and, if the linefrequency to be employed for the dotting process is higher than thatline frequency, the stability of the dots to be reproduced through thedotting process is reduced. That is, even if an attempt is made tofaithfully reproduce the halftone dots with a line frequency greaterthan the line frequency to be employed for the dotting process in thehalftoning process in the image outputting apparatus, the dots cannotstably be formed. A recent trend is to process an image at 600 dpi,which may depend on the image outputting apparatus and the linefrequency to be employed for the halftoning process. The dot stabilitycan generally be ensured if a difference between the line frequency forthe halftoning process and the line frequency of a thin line image in adocument original is within ±50 lpi.

[0090] For the prevention of a morié pattern, on the other hand, it ispreferred that the line frequency for the dotting process in thehalftoning process is not close to the line frequency of the halftonedot image of the document original to be subjected to the imageprocessing. As these line frequencies are closer to each other, a moreconspicuous morié pattern is liable to occur. In general, virtually nomorié pattern occurs if the line frequency for the halftoning process is±50 lpi apart from the line frequency of the image of the documentoriginal.

[0091] A higher-line-frequency image such as a photograph image isgenerally subjected to the dotting process. Therefore, a boundary linefrequency to be employed for the area separation in the halftoningprocess is defined between the line frequency for the halftoning process(for the dotting process) and this line frequency plus 50 lpi (forexample, at 175 lpi). An image area with a line frequency higher thanthe boundary line frequency is regarded as the photograph image area,and an image area with a line frequency not higher than the boundaryline frequency is excluded from the photograph image area.

[0092] Where the line frequency of the halftone dot image of thedocument original is close to the line frequency of the halftone dotimage to be formed through the improved error diffusion process in thehalftoning section 37 with a line frequency difference there betweenbeing relatively small within ±50 lpi, there is a possibility that aso-called morié pattern is formed in an outputted image. Therefore,pixels in a document original image with such a line frequency arepreferably subjected not to the improved error diffusion process but tothe ordinary error diffusion process employing the quantizationthresholds each fixed at a predetermined value. On the other hand, ahalftone dot image with a line frequency higher than the boundary linefrequency defined between 141 lpi (the line frequency to be employed forthe improved error diffusion process) and 141+50 lpi is regarded as aphotograph image and subjected to the improved error diffusion processfor proper gradation representation.

[0093] Therefore, the boundary line frequency is defined between thepredetermined line frequency (141 lpi in this embodiment) to be employedfor the improved error diffusion process and this line frequency plus 50lpi (191 lpi in this embodiment). An image with a line frequency notlower than the boundary line frequency is judged to belong to thephotograph image area, while an image with a line frequency lower thanthe boundary line frequency is judged to belong to any of the otherimage areas. The boundary line frequency is determined depending on theconfiguration of the pre-separation filtering section 39. Morespecifically, a line frequency possibly causing the interference isreduced to reduce the boundary line frequency, as the size of the matrixshown in FIG. 8(a) is increased. If the factors s1 to s6 in the matrixare differentiated (for example, with the factor at the center havingthe highest value), the boundary line frequency is increased. In thisembodiment where the factors s1 to s6 are set at the same value with thematrix shown in FIG. 8(a), the boundary line frequency is about 175 lpi.

[0094] As shown in FIG. 9, the integration filter in the pre-separationfiltering section 39 is configured so that image data of a 141-lpihalftone dot image in the document original subjected to the integrationfiltering process is free from an interference between halftone dots(halftone dots subjected to the smoothing process are diagonally shadedin FIG. 9). The integration filter is adapted to cause a properinterference between adjacent halftone dots in the case where theinputted image is a halftone dot image with a line frequency of notlower than 175 lpi. As a result, the area separating section 38 judgesthat the sum of the image data differences between the pixels in the13×7 pixel matrix for the higher-line-frequency halftone dot image witha line frequency of not lower than 175 lpi is relatively small and,hence, the pixels in the higher-line-frequency halftone dot imagebelongs to the photograph image area.

[0095] It is noted that the first image block and the second image blockare not necessarily required to be the 13×7 pixel matrix and the 5×5pixel matrix, respectively.

[0096] That is, the size of the first image block is determined so thatthe distributions of the plots indicative of the relationship betweenthe average value AV and the image data difference sum TOTAL_SUM in thefirst image block appear in the separate regions as shown in FIG. 6.

[0097] In this embodiment, the 13×7 pixel matrix is employed as thefirst image block as described above. This is because a reference ismade to a region which assuredly contains a constituent halftone dot ofa 65-lpi halftone dot image. An example of the 65-lpi halftone dot imageis a photograph image printed on newspaper, and the minimum linefrequency to be employed for ordinary printed matter is 65 lpi.Therefore, the minimum requirement for practical applications is todiscriminate halftone dot image areas with a line frequency of notsmaller than 65 lpi from the photograph image area.

[0098] For this purpose, at least one constituent halftone dot of the65-lpi halftone dot image should be present in the reference region(first image block). Where halftone dots D are present at a screen angleof 45 degrees as shown in FIG. 10, a distance between adjacent halftonedots D aligning in the main scanning direction is {square root}{squareroot over ( )}2/65 inch, and a distance between adjacent dots D aligningin the sub-scanning direction is 1/(65·{square root}{square root over ()}2 ) inch.

[0099] Where the reading section 1 has a reading resolution of 600 dpi,the distance between the adjacent dots D aligning in the main scanningdirection corresponds to 13 pixels (≈600×{square root}{square root over( )}2/65 ), and the distance between the adjacent dots D aligning in thesub-scanning direction corresponds to 7 pixels (≈6.53=600/(65·{squareroot}{square root over ( )}2)). Therefore, a halftone dot image with aline frequency of not lower than 65 lpi can be discriminated from thephotograph image area by setting the size of the first image block tothe 13×7 pixel matrix as described above.

[0100] As can be understood from the forgoing, the size of the firstimage block depends on the line frequency of the halftone dot image tobe separated and the reading resolution of the reading section 1, andthe 13×7 pixel matrix is merely an example of the first image block.

[0101] In order to reduce the capacity of the buffer memory required fordefining the first image block, the size of the first image block ispreferably determined so that one halftone dot in a halftone dot imagewith the minimum line frequency to be separated is present in thereference matrix. Alternatively, the size of the first image block maybedetermined so that more than one halftone dot (the number of thehalftone dots is not necessarily required to be an integer) is presentin the first image block. For the discrimination of the halftone dotimage with a line frequency of not lower than 65 lpi from the photographimage area, a matrix having a size greater than the 13×7 pixel matrixmay be employed as the first image block.

[0102] Similarly, the size of the pixel matrix to be employed as thesecond image block is determined so that the distributions of the plotsindicative of the relationship between the main scanning directiondensity difference sum H_SUM and the sub-scanning direction densitydifference sum V_SUM for the image to be regarded as belonging to thephotograph image area and for the image in the thin line image area arepresent in separate regions in the distribution graph shown in FIG. 7.Therefore, the second image block may be a square pixel matrix smalleror greater than the 5×5 pixel matrix, a rectangular matrix withdifferent numbers of pixels aligning in the main scanning direction andin the sub-scanning direction, or a matrix of any other configuration.For example, the 13×7 pixel matrix employed as the first image block maybe employed as it is as the second image block, and TOTAL_DH andTOTAL_DV maybe employed instead of H_SUM and V_SUM, respectively.

[0103] Where the reference matrix has a greater size, however, there isa possibility that the judgment for the area separation is erroneouslymade, because pixels in each line are initially processed with referenceto a smaller number of image data. In this connection, matrices ofminimum necessary sizes are preferably employed as the first image blockand the second image block.

[0104] Pixels located in opposite end portions with respect to the mainscanning direction and the sub-scanning direction are insufficient todefine the first image block or the second image block. Where the firstpixel in each line is to be processed as the object pixel, for example,no pixel is present upstream of the object pixel in the main scanningdirection. In such a case, image data of null pixels in the 13×7 pixelmatrix or the 5×5pixel matrix is regarded as “0” for the judgment forthe area separation.

[0105]FIG. 11 is a block diagram for explaining the functionalconfiguration of the halftoning section 37. The halftoning section 37includes a parameter generating section 51 for generating parameters forthe error diffusion process on the basis of the area separation signalapplied from the area separating section 38, the coordinates of theobject pixel and the image data of the object pixel (the image datasubjected to the output γ correction process in this embodiment). Thehalftoning section 37 further includes an error diffusion processingsection 52 for performing an error diffusion computation on the inputtedimage data on the basis of the image data applied from the outputγcorrection section 36 and the various parameters applied from theparameter generating section 51.

[0106] The parameter generating section 51 has a construction (whichwill be described later) adapted to generate thresholds V1, V2 and V3,or F1, F2 and F3 to be employed for the quantization of the inputtedimage data (for the two-level or four-level quantization of the inputtedimage data in this embodiment) and an error correction value EC to beemployed for the correction of the error generated when the image datais quantized (quantization error), and apply the thresholds and theerror correction value to the error diffusion processing section 52.

[0107] The error diffusion processing section 52 includes an erroradding section 61 for adding a cumulative error stored in a cumulativeerror memory 62 to the inputted image data. The cumulative error memory62 cumulatively stores therein errors distributed to the object pixelfrom peripheral pixels subjected to the quantization process. As shownin FIG. 12(a), errors from quantized peripheral pixels a, b, c, d, e andf, for example, are each multiplied by a predetermined error diffusionfactor (e.g., ¼ or ⅛) for an object pixel X, and summed up. In thiscase, the cumulative error is calculated, for example, from thefollowing expression:

Cumulative error=(⅛)×a+(¼)×b+(⅛)×c+(⅛)×d+(⅛)×e+(¼)×f  (8)

[0108] Cumulative errors are stored for the respective pixels in thecumulative error memory 62, and the cumulative error for the objectpixel to be subjected to the error diffusion process is read out of thecumulative error memory 62 and added to the image data of the objectpixel by the error adding section 61.

[0109] The error diffusion processing section 52 further includes aquantizing section 63 for quantizing the image data subjected to theerror adding process on the basis of the three quantization thresholdsV1, V2 and V3, or F1, F2 and F3 applied from the parameter generatingsection 51 for the ordinary error diffusion process or for the improvederror diffusion process. In this embodiment, the quantizing section 63converts the image data into 2-bit data representing one of four values(i.e., 0, 1, 2, 3).

[0110] The quantization thresholds V1, V2, V3 are variable thresholdswhich are defined to be periodically two-dimensionally variable in animage plane and satisfy a relationship of V1≦V2≦V3. The quantizationthresholds F1, F2, F3 are fixed thresholds which are defined to satisfya relationship of F1≦F2≦F3 (particularly, F1=F2=F3 in this embodiment).The parameter generating section 51 generates the variable thresholds V,V2, V3 or the fixed thresholds F1, F2, F3. Upon reception of thequantization thresholds, the quantizing section 63 performs thefollowing conditional judgment steps I, II, III, IV in this order on thebasis of the three quantization thresholds V, V2 and V3, or F1, F2 andF3 to quantize the image data into 0, 1, 2 or 3 (four-levelquantization). If any of the conditions is first satisfied when theconditional judgment steps I to IV are performed in sequence, a value(output data) is determined for the quantization without performing thesubsequent conditional step.

[0111] I. If (Image data subjected to the error adding process)>V3 orF3, the image data of the object pixel is quantized into “3”.

[0112] II. If V3 or F3≦(Image data subjected to the error addingprocess)>V2 or F2, the image data of the object pixel is quantized into“2”.

[0113] III. If V2 or F2≦(Image data subjected to the error addingprocess)>V1 or F1, the image data of the object pixel is quantized into“1”.

[0114] IV. If V1 or F1≦(Image data subjected to the error addingprocess), the image data of the object pixel is quantized into “0”. . .(9)

[0115] Where the quantization thresholds V1, V2 and V3, or F1, F2 and F3have different values, the image data of the object pixel is quantizedon a four-level basis into 0, 1, 2 or 3. Where the quantizationthresholds V1, V2 and V3, or F1, F2 and F31 have the same value, theimage data of the object pixel is quantized on a two-level basis into 0or 3 by performing the conditional judgment steps I-IV in sequence.

[0116] An error generated as the result of the quantization processperformed by the quantizing section 63 is determined by an errorcalculating section 64. Where the density gradation of the inputtedimage data is represented on the basis of 256 gradation levels from 0 to255, the error calculating section 64 calculates the error on the basisof the output data (the result of the quantization) from the followingexpressions:

[0117] If the output data is 3,

Error=(Image data subjected to error adding process) −255(Maximumgradation level);

[0118] If the output data is 2,

Error=(Image data subjected to error adding process) −170(Secondintermediate gradation level);

[0119] If the output data is 1,

Error=(Image data subjected to error adding process) −85(Firstintermediate gradation level);

[0120] If the output data is 0,

Error=(Image data subjected to error adding process) −0(Minimumgradation level)  (10)

[0121] The output data “3” corresponds to a black pixel of the maximumgradation level “255”. The output data “0” corresponds to a white pixelof the minimum gradation level “0”. The output data “1” and “2”correspond to gray pixels of the first intermediate gradation level “85”and the second intermediate gradation level “170”, respectively. Thefirst intermediate gradation level and the second intermediate gradationlevel are set at the gradation levels which equally divide the fullgradation range from 0 to 255 into three ranges.

[0122] The error calculated by the error calculating section 64 issubjected to a correction process to be performed by an error correctionsection 65. The correction process is performed by subtracting the errorcorrection value EC applied from the parameter generating section 51from the error determined by the error calculating section 64 as shownin the following expression (11). The corrected error is subjected to adistribution process to be performed by an error distributing section66. A cumulative error obtained as the result of the distributionprocess is stored in the cumulative error memory 62.

Corrected error=(Error calculated from expression (10)−EC  (11)

[0123] The process to be performed by the error distributing section 66is reverse to the error accumulating process shown in FIG. 12(a). Thatis, the error generated for the object pixel X is multiplied by apredetermined error diffusion factor (¼ or ⅛ in this embodiment) asshown in FIG. 12(b) and distributed to peripheral pixels yet to besubjected to the two-level quantization process around the object pixelX.

[0124]FIG. 13 is a block diagram for explaining the functionalconfiguration of the parameter generating section 51. On the basis ofthe area separation signal applied from the area separating section 38,the parameter generating section 51 generates parameters for theordinary error diffusion process employing the quantization thresholdseach fixed at a predetermined value and parameters for the improvederror diffusion process employing the quantization thresholdsperiodically two-dimensionally variable in the image plane. Morespecifically, where the area separation signal has a value of 1 whichindicates that the object pixel belongs to the photograph image area,the parameters for the improved error diffusion process are generated.Where the area separation signal has a value of 0 which indicates thatthe object pixel belongs to any of the image areas other than thephotograph image area, the parameters for the ordinary error diffusionprocess are generated.

[0125] For this function, the parameter generating section 51 includes afixed threshold setting section 71 for generating the fixed thresholdsF1, F2, F3 for the ordinary error diffusion process, a variablethreshold setting section 72 for generating the variable thresholds V1,V2, V3 for the improved error diffusion process, a threshold selectingsection 73 for selecting the fixed thresholds F1, F2, F3 or the variablethresholds V1, V2, V3 on the basis of the area separation signal, and acorrection value calculating section 74 for calculating the errorcorrection value EC for the correction of the error and applying theerror correction value EC to the error diffusion processing section 52.

[0126] The correction value calculating section 74 calculates the errorcorrection value EC on the basis of the area separation signal and thevariable thresholds V, V2, V3 applied from the variable thresholdsetting section 72. More specifically, where the area separation signalhas a value of 0 and the object pixel belongs to any of the image areasother than the photograph image area, the error correction value EC isset at a fixed value (0 in this embodiment). On the other hand, wherethe area separation signal has a value of 1, the error correction valueEC is variably set in accordance with the values of the variablethresholds V1, V2, V3 applied from the variable threshold settingsection 72.

[0127] In this embodiment, the fixed thresholds F1, F2, F3 generated bythe fixed threshold setting section 71 are set at the same value (e.g.,127 which is a middle value between 0 and 255). When the fixedthresholds F1, F2, F3 are applied to the error diffusion processingsection 52, the quantizing section 63 of the error diffusion processingsection 52 quantizes the inputted image data on a two-level basis into 0or 3.

[0128] The variable threshold setting section 72 includes a variablethreshold matrix memory 80 storing therein a variable threshold matrixfor setting the quantization thresholds periodically two-dimensionallyvariable in the image plane, a variable threshold selection informationgenerating section 85 for determining the position of the object pixelwithin the variable threshold matrix on the basis of the coordinates ofthe object pixel and generating a matrix element value at that positionin the variable threshold matrix as variable threshold selectioninformation, and a variable threshold generating section 86 forgenerating the variable thresholds V1, V2, V3 on the basis of thevariable threshold selection information and the value of the image dataof the object pixel.

[0129] The variable threshold generating section 86 includes a variablethreshold memory 81 storing therein a variable threshold table T1 forthe generation of the variable threshold V1, a variable threshold memory82 storing therein a variable threshold table T2 for the generation ofthe variable threshold V2, and a variable threshold memory 83 storingtherein a variable threshold table T3 for the generation of the variablethreshold V3. The variable threshold generating section 86 furtherincludes a variable threshold selecting section 84 for selecting thevariable thresholds V1, V2 and V3 from the variable threshold memories81, 82 and 83, respectively, on the basis of the variable thresholdselection information and the value of the image data of the objectpixel and applying the selected variable thresholds to the thresholdselecting section 73.

[0130] Where the area separation signal has a value of 1 indicative ofthe attribution to the photograph image area, the threshold selectingsection 73 selects the variable thresholds V1, V2, V3 and applies thevariable thresholds to the error diffusion processing section 52. Wherethe area separation signal has a value of 0 indicative of theattribution to any of the image areas other than the photograph imagearea, the threshold selecting section 73 applies the fixed thresholdsF1, F2, F3 set by the fixed threshold setting section 71 to the errordiffusion processing section 52.

[0131]FIG. 14(a) is a diagram illustrating an example of the variablethreshold matrix stored in the variable threshold matrix memory 80, andFIG. 14(b) is a diagram illustrating addresses of the variable thresholdmatrix memory 80 corresponding to respective matrix positions in thevariable threshold matrix. FIG. 14(a) illustrates the variable thresholdmatrix prepared in consideration of the four-level quantization of theimage data, and the values of the respective matrix elements are eachset at 0, 1, 2 or 3. Relatively small quantization thresholds are setfor a pixel corresponding to a smaller matrix element value in thethreshold matrix. Relatively great quantization thresholds are set for apixel corresponding to a greater matrix element value in the thresholdmatrix. Therefore, if the object pixel corresponds to a smaller matrixelement value, there is a high possibility that the object pixel isquantized into a value indicative of a high density pixel (black pixel).If the object pixel corresponds to a greater matrix element value, thereis a high possibility that the object pixel is quantized into a valueindicative of a low density pixel (white pixel).

[0132] The quantization process to be performed on the image byemploying the variable thresholds V1, V2, V3 can be understood byimagining that variable threshold matrices as shown in FIG. 14(a) aretwo-dimensionally tiled over the image plane. In this case, thequantization thresholds to be employed by the quantizing section 63 (seeFIG. 11) are periodically variable in the main scanning direction andthe sub-scanning direction (i.e., two-dimensionally). Therefore, dots(halftone dots) periodically appear in an image obtained through thequantization process and, as a result, the dotting process can beachieved.

[0133] In FIG. 14(a), a small 3×3 pixel matrix with a matrix element ofa value “0” (corresponding to a saddle point in a quantization thresholdvariation cycle) surrounded by matrix elements of a value “1” and asmall 3×3 pixel matrix with a matrix element of a value “3”(corresponding to a peak point in the quantization threshold variationcycle) surrounded by matrix elements of a value “2” are alternatelyarranged in the main scanning direction and the sub-scanning direction.Thus, halftone dots can be formed at a screen angle of 45 degrees. Wherethe reading section 1 has a reading resolution of 600 dpi, the halftonedot image has a line frequency of 141 lpi.

[0134] Although the variable threshold matrix shown in FIG. 14(a) isconstituted by 6×6 pixels, the size of the matrix may be 5×5 pixels, 7×7pixels or the like. Where the size of an n×n pixel matrix is defined as“n”, for example, the position of the object pixel in the variablethreshold matrix (i.e., the address of the object pixel in the variablethreshold matrix memory 80) can be calculated from the followingexpression on the basis of the coordinates of the object pixel (mainscanning coordinate, sub-scanning coordinate).

Address=[Remainder of (Main scanning coordinate÷n)) +(Remainder of(Sub-scanning coordinate÷n)]×8

[0135] In this expression, it is assumed that the maximum matrix size ofthe variable threshold matrix is 8 (see FIG. 14(b)), and the variablethreshold matrix memory 80 may be addressed in a different mannerdepending on the configuration thereof.

[0136] The variable threshold selection information generating section85 reads a matrix element value from the variable threshold matrix onthe basis of the address calculated from the expression (12) with thecoordinates of the object pixel, and applies the matrix element value asthe variable threshold selection information to the variable thresholdselecting section 84. The variable threshold selecting section 84properly reads the variable thresholds V1, V2 and V3 from the variablethreshold tables T1, T2 and T3 of the variable threshold memories 81, 82and 83, respectively, on the basis of the variable threshold selectioninformation applied thereto.

[0137]FIG. 15 is a diagram illustrating exemplary settings of thevariable threshold tables T1, T2 and T3. The variable thresholds V1, V2,V3 are defined so as to satisfy the relationship V1≦V2≦V3.

[0138] More specifically, the variable thresholds V1(0) V2(0),V3(0) fora matrix element value of 0 in the variable threshold matrix are inprinciple determined so as to satisfy a relationship ofV1(0)=V2(0)=V3(0) in this embodiment. Similarly, the variable thresholdsV1, V2, V3 for matrix element values of 2 and 3 in the variablethreshold matrix are in principle determined so as to satisfyrelationships of V1(2)=V2(2)=V3(2) and V1(3)=V2(3)=V3(3).

[0139] The variable thresholds V1(1), V2(1), V3(1) for a specific matrixelement value of 1 in the variable threshold matrix are in principledetermined so as to satisfy a relationship of V1(1)<V2(1)<V3(1).

[0140] In principle, a smaller value is assigned to each of the variablethresholds V1, V2, V3, as the matrix element value in the variablethreshold matrix is smaller. That is, the variable thresholds V1, V2, V3are determined so as to satisfy the following expressions:

V1(0)<V1(1)<V1(2)<V1(3)

V2(0)<V2(1)<V2(2)<V2(3)

V3(0)<V3(1)<V3(2)<V3(3)  (12)

[0141] Where the matrix element value in the variable threshold matrixis 0, 2 or 3 when the variable thresholds V1, V2, V3 are applied as thequantization thresholds to the quantizing section 63 of the errordiffusion processing section 52, the quantizing section 63 quantizes theinputted image data on a two-level basis into 0 or 3, because thevariable thresholds V1, V2, V3 have the same value. On the other hand,the variable thresholds V1, V2, V3 have different values for the objectpixel corresponding to the matrix element value “1” in the variablethreshold matrix and, therefore, the quantizing section quantizes theinputted image on a four-level basis into 0, 1, 2 or 3.

[0142] As can be understood in view of image data values in the rangebetween 0 and 15 in FIG. 15, the variable thresholds V1, V2, V3 arevariably set depending on the value (density level) of the image data ofthe object pixel in this embodiment. More specifically, where the imagedata has a value in the range between 1 and 7, the variable thresholdsV1, V2, V3 are fixedly set at a middle gradation level “127” between 0and 255 regardless of the matrix element value in the variable thresholdmatrix. Thus, the ordinary error diffusion process without periodicvariation of the quantization thresholds is performed, so that thequantizing section 63 of the error diffusion processing section 52quantizes the inputted image data on a two-level basis into 0 or 3.

[0143] Where the image data of the object pixel has a value in the rangebetween 8 and 15, the variable thresholds V1, V2, V3 are set so thatvariations in the variable thresholds for the matrix element values inthe variable threshold matrix are smaller than in the case where theimage data has a value of 16 or greater.

[0144] By thus nullifying or reducing the variations in the thresholdsfor the matrix element values in the variable threshold matrix, the dotconcentration in a very low density image area can be suppressed oreliminated. Thus, a low density image area in a photograph image can bereproduced with excellent gradation representation with no conspicuousbig dot in the output image. At the same time, textures can besuppressed which may otherwise occur due to the variations in thequantization thresholds.

[0145] The variable threshold selecting section 84 reads out thevariable thresholds V1, V2, V3 from the variable threshold memories 81,82, 83, respectively, on the basis of the image data of the object pixeland the matrix element value for the object pixel in the variablethreshold matrix (variable threshold selection information), and appliesthese variable thresholds to the threshold selecting section 73.

[0146] Where the area separation signal has a value of 0 and the fixedthresholds F1, F2, F3 set by the fixed threshold setting section 71 areemployed, the correction value calculating section 74 sets the errorcorrection value EC at 0. On the other hand, where the area separationsignal has a value of 1 indicative of the attribution to the photographimage area, the correction value calculating section 74 obtains thevariable thresholds V1, V2, V3 from the threshold selecting section 73,and calculates the error correction value EC from the followingexpression:

Error correction value=(V1+V2+V3)÷3−127  (13)

[0147] That is, a deviation of the average of the variable thresholdsV1, V2 and V3 from the middle gradation level “127” is determined as theerror correction value EC, which is applied to the error correctionsection 65. The error correction section 65 subtracts the errorcorrection value EC from the error calculated by the error calculatingsection 64 for calculation of the corrected error (see the expression(11)).

[0148] Where the variable thresholds V1, V2, V3 periodicallytwo-dimensionally variable in the image plane are employed, thecorrection is made so that the error to be distributed to the peripheralpixels is not influenced by the variations in the quantizationthresholds. This correction process is actually intended to changereference values for the calculation of the error in accordance with thevariations in the quantization thresholds.

[0149] That is, the minimum gradation level “0”, the first middlegradation level “85”, the second middle gradation level “170” and themaximum gradation level “255” in the expression (10) are the referencevalues for the calculation of the error. The process to be performed inaccordance with the expression (11) for the correction of the error isactually intended to correct the reference values “0”, “85”, “170” and“255 ” for the error calculation with the error correction value EC todetermine the quantization error with the use of the correctedcalculation reference values “0-EC”, “85-EC”, “170-EC” and “255-EC”. Ascan be understood from the expression (13), the error correction valueEC periodically varies with the periodic variation of the variablethresholds V1, V2, V3, so that the corrected calculation referencevalues periodically vary in phase with the variable thresholds V1, V2,V3. Thus, distribution of a greater error to the peripheral pixels canbe prevented, so that dots can effectively be concentrated for formationof a halftone dot.

[0150]FIG. 16 is a diagram illustrating the periodic variation of thequantization thresholds and the corresponding periodic variation of thereference values for the error calculation. When the quantizationthresholds (variable thresholds) V1, V2, V3 periodically vary asindicated by bold lines in FIG. 16, the error correction value EC whichis the deviation from the middle gradation level “127” varies asindicated by arrows in FIG. 16. In this case, downward arrows indicatethat the error correction value EC is negative, while upward arrowsindicate that the error correction value EC is positive.

[0151] For example, it is assumed that the variable thresholds V1=V2=V3for the matrix element value “0” in the variable threshold matrix areset lower than the middle level “127”. When the object pixel X has avalue smaller than the middle level “127” and greater than the variablethresholds V1, V2, V3, the object pixel X is quantized into 3 indicativeof a black pixel. At this time, the error calculating section 64calculates a pre-correction error from the following expression:

Pre-correction error=(Value of object pixel X after addition ofcumulative error)−255  (14)

[0152] In this case, an error having an absolute value greater than 127is generated. Therefore, the pre-correction error is corrected so as tohave a smaller absolute value by subtracting the error correction valueEC therefrom. As the result of the correction, the corrected error has asmaller value according to the quantization thresholds V1, V2, V3. Thiscorrection is equivalent to a correction by which the reference valuefor the error calculation is corrected into a value R(3) which issmaller than the maximum gradation level “255”.

[0153] In FIG. 16, a practical error calculation reference valueemployed when the image data of the object pixel is quantized intooutput data “0”, “1”, “2” or “3” is expressed as R(0), R(1), R(2) orR(3), respectively. Where the matrix element value in the variablethreshold matrix is 1, the four-level quantization process is performedwith the use of the variable thresholds V1, V2, V3 having differentvalues and, correspondingly, there are four error calculation referencevalues R(0) R(1), R(2), R(3).

[0154]FIG. 17 is a diagram for explaining an effect of a higher-levelquantization process (four-level quantization process in thisembodiment) to be performed only for the specific matrix element value(1 in this embodiment) in the variable threshold matrix. As describedabove, the quantization thresholds can periodically two-dimensionally bevaried by employing the variable threshold matrix shown in FIG. 14(a) Asa result, the gradation of the photograph image can be represented byhalftone dots with a predetermined line frequency (e.g., 141 lpi). Wherea dot DC is formed as a core of a halftone dot, the expansion orcontraction of the dot DC constituting the halftone dot can more finelybe controlled through the four-level quantization of the pixels aroundthe dot DC than through the two-level quantization of the pixels aroundthe dot DC. That is, the output section 4 including the laser scanningunit controls a laser emission period or a laser intensity for eachpixel at four levels on the basis of the image data quantized on afour-level (2-bit) basis, so that the size of the pixel to be recordedby the output section 4 can be controlled at four levels.

[0155] In this embodiment, a pixel (corresponding to the matrix elementvalue “1” in the variable threshold matrix) adjacent to the saddle point(corresponding to the matrix element value “0” in the variable thresholdmatrix) in the periodic variation cycle of the quantization thresholdsis subjected to the four-level quantization process. Thus, the dotexpansion and contraction levels can finely be defined as compared witha case where the quantization is performed only on a two-level basis,allowing for more smooth gradation representation.

[0156] Although the four-level quantization process is performed on apixel corresponding to the matrix element value “1” in the variablethreshold matrix in this embodiment, this arrangement is merely oneexample. The higher-level quantization process (four-level quantizationprocess in this embodiment) maybe performed on a pixel corresponding tothe matrix element value “2” in the variable threshold matrix, or onpixels corresponding to matrix element values “1” and “2” in thevariable threshold matrix.

[0157] In accordance with this embodiment, as described above, thepixels in the photograph image area can be extracted separately from thepixels in the other image areas on the basis of the result of themagnitude comparison between the sum TOTAL_SUM of the differences inimage data between the pixels in the first image block (13×7 pixelmatrix) containing the object pixel and the threshold TH(AV) determinedin accordance with the average value AV of the image data in the firstimage block.

[0158] The pixels in the thin line image area can be prevented frombeing erroneously judged to belong to the photograph image area bycomparing the sums H_SUM and V_SUM of the differences in the image dataof the pixels aligning in the main scanning direction and in thesub-scanning direction in the second image block (5×5 pixel matrix) withthe predetermined thresholds HL, HH, VL, VH. Therefore, the pixels inthe photograph image can be extracted very accurately.

[0159] The image data subjected to the smoothing process performed bythe pre-separation filtering section 39 is further subjected to theaforesaid area separating process, whereby the higher-line-frequencyhalftone dot image area (with a line frequency of not lower than 175lpi) can assuredly be judged to belong to the photograph image area.Thus, the higher-line-frequency halftone dot image which is virtuallyfree from a morié pattern when subjected to the dotting process(improved error diffusion process) in the halftoning section 37 can bereproduced with proper gradation representation as in the case of thephotograph image.

[0160] In this embodiment, the pixel judged to belong to the photographimage area is subjected to the improved error diffusion process byemploying the variable thresholds V1, V2, V3 which are periodicallytwo-dimensionally variable, whereby the dotting process can be performedon the higher-line-frequency halftone dot image with a line frequency ofnot lower than 175 lpi and the photograph image. Thus, the dotconcentration halftoning process advantageous for the image formationthrough the electrophotographic process can be employed, allowing forimage reproduction with excellent gradation representation.

[0161] On the other hand, the pixel judged not to belong to thephotograph image area is subjected to the ordinary error diffusionprocess by employing the quantization thresholds each fixed at apredetermined value, whereby the character image, the diagrammatic imageand the halftone dot image (with a lower line frequency) can bereproduced with a proper resolution, and are free from a morié pattern.

[0162] In the improved error diffusion process of this embodiment, thereference values for the error calculation can be varied in phase withthe variation of the quantization thresholds. This eliminates thepossibility that a great quantization error which may otherwise begenerated due to the variation of the quantization thresholds isdistributed to the peripheral pixels around the object pixel. Therefore,black pixels for forming each halftone dot can effectively beconcentrated, so that the dotting process can advantageously beperformed through the improved error diffusion process. It is anadditional advantage that the image density can assuredly be conserved.

[0163] In this embodiment, the peripheral pixels around the dot servingas the core of the halftone dot are subjected not to the two-levelquantization process but to the four-level quantization process, wherebythe dot expansion and contraction can be controlled at an increasednumber of levels. Therefore, the higher-line-frequency halftone dotimage and the photograph image can be reproduced with smooth gradationrepresentation.

[0164] While one embodiment of the present invention has thus beendescribed, the invention may be embodied in any other ways. Although thematrix element value for the higher-level quantization process(four-level quantization process) is set at a fixed value in theembodiment described above, the matrix element value for thehigher-level quantization process (four-level quantization process) maybe variably set on the basis of an average value of image data within athird image block (for example, a matrix region having substantially thesame size as the variable threshold matrix) containing the object pixel.In this case, a relationship between the average value of the image datain the third image block and the matrix element value may be defined asshown in Table 1, if the variable threshold matrix of FIG. 14(a) isemployed. TABLE 1 Average value Threshold matrix of image data elementvalue  0 − 63 0  64 − 127 1 128 − 191 2 192 − 255 3

[0165] With this arrangement, the four-level quantization process canassuredly be applied to pixels constituting the periphery of a dot(halftone dot) in any density region, allowing for more excellentgradation reproduction.

[0166] Although the error calculation reference values periodicallyvariable with the periodic variation of the quantization thresholds havea predetermined variation range with respect to the values of thevariable thresholds in the embodiment described above, the variationrange may be varied depending on the value of image data of a pixeladjacent to the object pixel. For example, the dot concentration can besuppressed in a lower density region by increasing the variation range,whereby incongruous dot concentration can be suppressed, allowing forexcellent image reproduction. On the other hand, dots can advantageouslybe concentrated in a high density region by reducing the variationrange, allowing for excellent gradation reproducibility.

[0167] In the embodiment described above, the quantization process isperformed selectively in two ways, i.e., on a two-level basis and on afour-level basis, but may be performed selectively in three or moreways. For example, the peripheral pixels around the pixel to besubjected to the two-level quantization process for formation of the dotcore may be subjected to a three-level quantization process, and pixelssurrounding the peripheral pixels may be subjected to the four-levelquantization process.

[0168] In the embodiment described above, the four-level quantizationprocess is performed for the peripheral pixels around the black pixel(the dot core pixel constituting the halftone dot), but may be performedfor pixels to be located around a white pixel, so that gray pixels(black pixels each having a smaller area) are formed around the whitepixel. In this case, the higher-level quantization process is performedon a pixel adjacent to a peak point in the quantization thresholdvariation cycle.

[0169] In the embodiment described above, the present invention isapplied to the digital copying machine, but may widely be applied toimage data processing apparatuses such as facsimile machines andprinters adapted to perform image processing operations on inputtedimage data to form an image on a recording sheet.

[0170] While the present invention has been described in detail by wayof the embodiment thereof, it should be understood that the foregoingdisclosure is merely illustrative of the technical principles of thepresent invention but not limitative of the same. The spirit and scopeof the present invention are to be limited only by the appended claims.

[0171] This application corresponds to Japanese Patent Application No.2000-287504 filed to the Japanese Patent Office on Sep. 21, 2000, thedisclosure thereof being incorporated herein by reference.

What is claimed is:
 1. An area separating apparatus for judging whetheror not each object pixel belongs to a photograph image area in an imageon the basis of image data indicative of density gradation levels ofpixels constituting the image, the apparatus comprising: an averagevalue calculating circuit for calculating an average value of image dataof pixels in a first image block of a predetermined size containing theobject pixel; a photograph image area judgment threshold generatingcircuit for generating a photograph image area judgment threshold inaccordance with the average value calculated by the average valuecalculating circuit; a density difference summing circuit fordetermining differences in image data between respective adjacent pairsof pixels in the image block and calculating a sum of the image datadifferences for all the pixels in the image block; and a first judgmentcircuit which judges that the object pixel belongs to the photographimage area if the sum of the image data differences calculated by thedensity difference summing circuit is smaller than the photograph imagearea judgment threshold generated by the photograph image area judgmentthreshold generating circuit, and judges that the object pixel does notbelong to the photograph image area if the sum of the image datadifferences is not smaller than the photograph image area judgmentthreshold.
 2. An area separating apparatus as set forth in claim 1,further comprising: a first direction density difference summing circuitfor determining differences in image data between respective adjacentpairs of pixels aligning in a first direction in a second image block ofa predetermined size containing the object pixel and summing the imagedata differences for all the pixels in the second image block fordetermination of a first direction density difference sum; a seconddirection density difference summing circuit for determining differencesin image data between respective adjacent pairs of pixels aligning in asecond direction different from the first direction in the second imageblock and summing the image data differences for all the pixels in thesecond image block for determination of a second direction densitydifference sum; a second judgment circuit for judging whether or not theobject pixel belongs to a thin line image area on the basis of amagnitude relationship between the first direction density differencesum and the second direction density difference sum respectivelycalculated by the first direction density difference summing circuit andthe second direction density difference summing circuit; and are-judgment circuit which re-judges that the object pixel belongs to thephotograph image area if the object pixel is judged to belong to thephotograph image area by the first judgment circuit and is judged not tobelong to the thin line image area by the second judgment circuit, andre-judges that the object pixel does not belong to the photograph imagearea if the object pixel is judged to belong to the photograph imagearea by the first judgment circuit and is judged to belong to the thinline image area by the second judgment circuit.
 3. An area separatingapparatus as set forth in claim 2, wherein the second judgment circuitcompares the first direction density difference sum calculated by thefirst direction density difference summing circuit and the seconddirection density difference sum calculated by the second directiondensity difference summing circuit with a pair of first directionjudgment thresholds HL, HH (HL<HH) and a pair of second directionjudgment thresholds VL, VH (VL<VH), respectively, and judges that theobject pixel belongs to the thin line image area if a condition that thefirst direction density difference sum is not smaller than the firstdirection judgment threshold HH and the second direction densitydifference sum is not greater than the second direction judgmentthreshold VL is satisfied, or if a condition that the first directiondensity difference sum is not greater than the first direction judgmentthreshold HL and the second direction density difference sum is notsmaller than the second direction judgment threshold VH is satisfied,and judges that the object pixel does not belong to the thin line imagearea if neither of the conditions is satisfied.
 4. An area separatingapparatus as set forth in claim 1, further comprising: an integratorcircuit for performing an integration process on image data of theobject pixel with the use of the image data of the object pixel andimage data of peripheral pixels around the object pixel, wherein ajudgment is made on the basis of the image data pre-processed by theintegrator circuit to determine which of the image areas the objectpixel belongs to.
 5. An area separating apparatus as set forth in claim1, wherein the image data is subjected to a halftoning process, whichincludes a dotting process to be performed on the basis of apredetermined line frequency on pixels judged to belong to thephotograph image area, the area separating apparatus further comprisinga pre-judgment circuit for performing a pre-judgment process to define aboundary line frequency between the predetermined line frequency and thepredetermined line frequency plus 50 lpi and exclude pixels constitutinga halftone dot image with a line frequency lower than the boundary linefrequency from the pixels judged to belong to the photograph image area.6. An area separating apparatus as set forth in claim 5, wherein thepre-judgment circuit performs the pre-judgment process on the image datato be subjected to the halftoning process.
 7. An area separatingapparatus as set forth in claim 5, wherein the pre-judgment circuitincludes an integration filter for performing a smoothing process on theimage data so as to cause halftone dots constituting a halftone dotimage with a line frequency not lower than the boundary line frequencyto contact one another.
 8. An area separating apparatus for judgingwhether or not each object pixel belongs to a thin line image area in animage on the basis of image data indicative of density gradation levelsof pixels constituting the image, the apparatus comprising: a firstdirection density difference summing circuit for determining differencesin image data between respective adjacent pairs of pixels aligning in afirst direction in a second image block of a predetermined sizecontaining the object pixel and summing the image data differences forall the pixels in the second image block for determination of a firstdirection density difference sum; a second direction density differencesumming circuit for determining differences in image data betweenrespective adjacent pairs of pixels aligning in a second directiondifferent from the first direction in the second image block and summingthe image data differences for all the pixels in the second image blockfor determination of a second direction density difference sum; and asecond judgment circuit for judging whether or not the object pixelbelongs to the thin line image area on the basis of a magnituderelationship between the first direction density difference sum and thesecond direction density difference sum respectively calculated by thefirst direction density difference summing circuit and the seconddirection density difference summing circuit.
 9. An image processingapparatus for processing image data indicative of density gradationlevels of pixels constituting an image in accordance with a judgment onwhether or not each object pixel belongs to a photograph image area inthe image, the apparatus comprising: an average value calculatingcircuit for calculating an average value of image data of pixels in afirst image block of a predetermined size containing the object pixel; aphotograph image area judgment threshold generating circuit forgenerating a photograph image area judgment threshold in accordance withthe average value calculated by the average value calculating circuit; adensity difference summing circuit for determining differences in imagedata between respective adjacent pairs of pixels in the image block andcalculating a sum of the image data differences for all the pixels inthe image block; a first judgment circuit which judges that the objectpixel belongs to the photograph image area if the sum of the image datadifferences calculated by the density difference summing circuit issmaller than the photograph image area judgment threshold generated bythe photograph image area judgment threshold generating circuit, andjudges that the object pixel does not belong to the photograph imagearea if the sum of the image data differences is not smaller than thephotograph image area judgment threshold; and a halftoning circuit forperforming a dot concentration halftoning process on pixels judged tobelong to the photograph image area and performing a dot distributionhalftoning process on pixels judged not to belong to the photographimage area.
 10. An image processing apparatus as set forth in claim 9,further comprising: a first direction density difference summing circuitfor determining differences in image data between respective adjacentpairs of pixels aligning in a first direction in a second image block ofa predetermined size containing the object pixel and summing the imagedata differences for all the pixels in the second image block fordetermination of a first direction density difference sum; a seconddirection density difference summing circuit for determining differencesin image data between respective adjacent pairs of pixels aligning in asecond direction different from the first direction in the second imageblock and summing the image data differences for all the pixels in thesecond image block for determination of a second direction densitydifference sum; a second judgment circuit for judging whether or not theobject pixel belongs to a thin line image area on the basis of amagnitude relationship between the first direction density differencesum and the second direction density difference sum respectivelycalculated by the first direction density difference summing circuit andthe second direction density difference summing circuit; and are-judgment circuit which re-judges that the object pixel belongs to thephotograph image area if the object pixel is judged to belong to thephotograph image area by the first judgment circuit and is judged not tobelong to the thin line image area by the second judgment circuit, andre-judges that the object pixel does not belong to the photograph imagearea if the object pixel is judged to belong to the photograph imagearea by the first judgment circuit and is judged to belong to the thinline image area by the second judgment circuit.
 11. An area separatingmethod for judging whether or not each object pixel belongs to aphotograph image area in an image on the basis of image data indicativeof density gradation levels of pixels constituting the image, the methodcomprising the steps of: calculating an average value of image data ofpixels in a first image block of a predetermined size containing theobject pixel; determining differences in image data between respectiveadjacent pairs of pixels in the image block and calculating a sum of theimage data differences for all the pixels in the image block; andperforming a first judgment process to judge that the object pixelbelongs to the photograph image area if the sum of the image datadifferences is smaller than a photograph image area judgment thresholddetermined in accordance with the average value, and to judge that theobject pixel does not belong to the photograph image area if the sum ofthe image data differences is not smaller than the photograph image areajudgment threshold.
 12. An area separating method as set forth in claim11, further comprising the steps of: determining differences in imagedata between respective adjacent pairs of pixels aligning in a firstdirection in a second image block of a predetermined size containing theobject pixel and summing the image data differences for all the pixelsin the second image block for determination of a first direction densitydifference sum; determining differences in image data between respectiveadjacent pairs of pixels aligning in a second direction different fromthe first direction in the second image block and summing the image datadifferences for all the pixels in the second image block fordetermination of a second direction density difference sum; performing asecond judgment process to judge whether or not the object pixel belongsto a thin line image area on the basis of a magnitude relationshipbetween the first direction density difference sum and the seconddirection density difference sum; and re-judging that the object pixelbelongs to the photograph image area if the object pixel is judged tobelong to the photograph image area in the first judgment step and isjudged not to belong to the thin line image area in the second judgmentstep, and re-judging that the object pixel does not belong to thephotograph image area if the object pixel is judged to belong to thephotograph image area in the first judgment step and is judged to belongto the thin line image area in the second judgment step.
 13. An areaseparating method as set forth in claim 12, wherein the second judgmentstep comprises the steps of: comparing the first direction densitydifference sum and the second direction density difference sum with apair of first direction judgment thresholds HL, HH (HL<HH) and a pair ofsecond direction judgment thresholds VL, VH (VL<VH), respectively; andjudging that the object pixel belongs to the thin line image area if acondition that the first direction density difference sum is not smallerthan the first direction judgment threshold HH and the second directiondensity difference sum is not greater than the second direction judgmentthreshold VL is satisfied, or if a condition that the first directiondensity difference sum is not greater than the first direction judgmentthreshold HL and the second direction density difference sum is notsmaller than the second direction judgment threshold VH is satisfied,and judging that the object pixel does not belong to the thin line imagearea if neither of the conditions is satisfied.
 14. An area separatingmethod as set forth in claim 11, further comprising the step of:performing an integration process on image data of the object pixel withthe use of the image data of the object pixel and image data ofperipheral pixels around the object pixel, wherein a judgment is made onthe basis of the image data pre-processed in the integration step todetermine which of the image areas the object pixel belongs to.
 15. Anarea separating method as set forth in claim 11, wherein the image datais subjected to a halftoning process, which includes a dotting processto be performed on the basis of a predetermined line frequency on pixelsjudged to belong to the photograph image area, the area separatingmethod further comprising the step of performing a pre-judgment processto define a boundary line frequency between the predetermined linefrequency and the predetermined line frequency plus 50 lpi and excludepixels constituting a halftone dot image with a line frequency lowerthan the boundary line frequency from the pixels judged to belong to thephotograph image area.
 16. An area separating method as set forth inclaim 15, wherein the pre-judgment process is performed on the imagedata to be subjected to the halftoning process in the pre-judgment step.17. An area separating method as set forth in claim 15, wherein thepre-judgment step comprises the step of performing a smoothing processon the image data so as to cause halftone dots constituting a halftonedot image with a line frequency not lower than the boundary linefrequency to contact one another.
 18. An area separating method forjudging whether or not each object pixel belongs to a thin line imagearea in an image on the basis of image data indicative of densitygradation levels of pixels constituting the image, the method comprisingthe steps of: determining differences in image data between respectiveadjacent pairs of pixels aligning in a first direction in a second imageblock of a predetermined size containing the object pixel and summingthe image data differences for all the pixels in the second image blockfor determination of a first direction density difference sum;determining differences in image data between respective adjacent pairsof pixels aligning in a second direction different from the firstdirection in the second image block and summing the image datadifferences for all the pixels in the second image block fordetermination of a second direction density difference sum; andperforming a second judgment process to judge whether or not the objectpixel belongs to the thin line image area on the basis of a magnituderelationship between the first direction density difference sum and thesecond direction density difference sum.